In the consumer electronics and computer industries, wireless sensor networks have been studied for many years. In archetypal wireless sensor networks, one or more sensors are implemented in conjunction with a radio to enable wireless collection of data from one or more sensor nodes deployed within a network. Each sensor node may include one or more sensors, and will include a radio and a power source for powering the operation of the sensor node. Location detection of nodes in indoor wireless networks is useful and important in many applications.
Localization based on triangulation performed using radio frequency measurements is an attractive method for determining location of wirelessly equipped objects in three dimensional space. RF-based localization may be performed in numerous ways. Distances between multiple object pairs must be determined to enable calculation of relative positions in three dimensional space via triangulation methods (e.g., least squares, global search, gradient descent) based on the individual pair distances. An exemplary implementation includes a hub and multiple sensor nodes. Note that the hub may be replaced with a node, or indeed, one or more of the nodes may be replaced with a hub. Distances are estimated using radio frequency techniques between all the individual pairs via RF communications. Once the distance is estimated, triangulation may be used to determine the relative position in three dimensional space of each object. If the position of at least 2 of the objects is known in real space, then the absolute position of each object in the network may be determined. Indeed, if the position of 1 object (e.g., the hub) is known within the network, along with the angular path to at least one other node, then again the absolute position of each object within the network may be determined.
Distance measurement between object pairs is therefore a key step in RF-based localization. Distance estimation may be performed in numerous ways. Signal strength of communication (RSSI) may be measured between pairs and used to estimate distance based on known models of signal attenuation. Time of Flight (TOF) may be measured for signals transmitted between objects and distance may be estimated based on known propagation delay models. Angle of arrival (AOA) may additionally be estimated based on resolution of angular variation in signal strength. Of these, RSSI is often prone to error due to variations in attenuation, and is therefore less attractive than TOF for distance estimation.
TOF based distance estimation is susceptible to error due to reflections causing the presence of multiple paths between two objects. In this situation, the estimated path may be detected as being longer than the real path due to the reflected path being longer than the direct path. If the system estimates the TOF based on the reflected path, then errors are introduced in triangulation.